At OneStudyTeam, the business problem is to speed up clinical trials and increase the chance of new therapies being approved by improving patient outcomes. The technical problem is to develop statistical models and machine learning algorithms to improve patient enrollment and trial management within a highly regulated healthcare data environment, ensuring compliance with privacy standards while innovating on predictive analytics.
Requirements
- Strong foundation in statistical modeling and machine learning techniques, including experience with Bayesian methods, regression analysis, and time-series forecasting.
- Proficiency in evaluating model performance and bias, with the ability to implement AI monitoring tools and bias mitigation strategies to ensure ethical and reliable outcomes.
- Advanced programming skills in Python (with libraries such as scikit-learn, PyMC, mlforecast, etc.) and SQL, as well as familiarity with data transformation tools like dbt.
- Hands-on experience with cloud-based analytics and ML services, especially AWS tools (Athena for querying, Redshift for data warehousing, SageMaker for model development/deployment).
- Experience working with sensitive healthcare or clinical trial data under regulations like HIPAA and GDPR, demonstrating a deep commitment to data privacy and security best practices.
- Understanding of clinical research or health-tech environments is highly valuable, including insight into clinical trial operations and a passion for improving patient outcomes through data.
Responsibilities
- Develop/enhance forecasting models for site randomization and enrollment trends, enabling better planning and resource allocation across trial sites.
- Support projects to build algorithms that intelligently match patients to (or rank patients for) appropriate clinical trials, enhancing recruitment efficiency and patient inclusion.
- Create and refine predictive models (Bayesian inference, regression analysis, time-series forecasting) to address other key clinical trial challenges and improve decision-making.
- Implement processes to monitor machine learning models in production, detecting bias or performance drift and ensuring models remain fair, accurate, and compliant.
- Build and optimize data pipelines and analytical workflows using tools like AWS Athena, Redshift, SageMaker, and dbt, enabling scalable model training and deployment.
- Ensure all data science practices align with HIPAA, GDPR, and other privacy regulations, integrating compliance considerations into model development and data handling.
- Work closely with machine learning engineers, product managers, and other stakeholders to integrate models into products and clearly communicate insights and recommendations.
Other
- 5+ years of hands-on data science or analytics experience, preferably in a healthcare, clinical research, or other highly regulated data environment.
- Excellent teamwork and meticulous verbal/written communication abilities, with a track record of partnering with engineering and product teams to translate data science work into actionable business solutions.
- Master’s or Ph.D. in Statistics, Data Science, Computer Science, or a related quantitative field (or equivalent professional experience).
- OneStudyTeam is unable to sponsor work visas at this time.
- As a condition of employment, you will abide by all organizational security and privacy policies.
